Delineating mouse β-cell identity during lifetime and in diabetes with a single cell atlas
Although multiple pancreatic islet single-cell RNA-sequencing (scRNA-seq) datasets have been generated, a consensus on pancreatic cell states in development, homeostasis and diabetes as well as the value of preclinical animal models is missing. Here, we present an scRNA-seq cross-condition mouse islet atlas (MIA), a curated resource for interactive exploration and computational querying. We integrate over 300,000 cells from nine scRNA-seq datasets consisting of 56 samples, varying in age, sex and diabetes models, including an autoimmune type 1 diabetes model (NOD), a glucotoxicity/lipotoxicity type 2 diabetes model (db/db) and a chemical streptozotocin β-cell ablation model. The β-cell landscape of MIA reveals new cell states during disease progression and cross-publication differences between previously suggested marker genes. We show that β-cells in the streptozotocin model transcriptionally correlate with those in human type 2 diabetes and mouse db/db models, but are less similar to human type 1 diabetes and mouse NOD β-cells. We also report pathways that are shared between β-cells in immature, aged and diabetes models. MIA enables a comprehensive analysis of β-cell responses to different stressors, providing a roadmap for the understanding of β-cell plasticity, compensation and demise.
Citation
@article{hrovatin2023,
author = {Hrovatin, Karin and Bastidas-Ponce, Aimée and Bakhti,
Mostafa and Zappia, Luke and Büttner, Maren and Sallino, Ciro and
Sterr, Michael and Böttcher, Anika and Migliorini, Adriana and
Lickert, Heiko and J Theis, Fabian},
title = {Delineating Mouse β-Cell Identity During Lifetime and in
Diabetes with a Single Cell Atlas},
journal = {Nature Metabolism},
volume = {5},
number = {1},
pages = {1615-1637},
date = {2023-09-11},
url = {https://lazappi.id.au/publications/2023-hrovatin-MIA},
doi = {10.1038/s42255-023-00876-x},
issn = {2522-5812},
langid = {en},
abstract = {Although multiple pancreatic islet single-cell
RNA-sequencing (scRNA-seq) datasets have been generated, a consensus
on pancreatic cell states in development, homeostasis and diabetes
as well as the value of preclinical animal models is missing. Here,
we present an scRNA-seq cross-condition mouse islet atlas (MIA), a
curated resource for interactive exploration and computational
querying. We integrate over 300,000 cells from nine scRNA-seq
datasets consisting of 56 samples, varying in age, sex and diabetes
models, including an autoimmune type 1 diabetes model (NOD), a
glucotoxicity/lipotoxicity type 2 diabetes model (db/db) and a
chemical streptozotocin β-cell ablation model. The β-cell landscape
of MIA reveals new cell states during disease progression and
cross-publication differences between previously suggested marker
genes. We show that β-cells in the streptozotocin model
transcriptionally correlate with those in human type 2 diabetes and
mouse db/db models, but are less similar to human type 1 diabetes
and mouse NOD β-cells. We also report pathways that are shared
between β-cells in immature, aged and diabetes models. MIA enables a
comprehensive analysis of β-cell responses to different stressors,
providing a roadmap for the understanding of β-cell plasticity,
compensation and demise.}
}